A natural scene usually contains some smoothly changing areas where the luminance is changing gradually. When the scene is recorded by a digital device such as a video camera, because of digitization (i.e., quantization of the luminance value for each pixel in an area), the digitalized picture of the smoothly changing area may include quantization artifacts, whereby the area no longer appears smooth. Instead, quantization artifacts, such as stage-like false contours, may be perceived. The magnitude of quantization artifacts is determined by the quantization accuracy in an A/D converter of the digitization device. This magnitude is not necessarily the same as the smallest step of the digitization devices, in fact, it is usually much larger and makes the quantization artifacts more obvious to human vision systems.
To eliminate this type of quantization artifacts, first their location in the digital image is determined, and then smoothing is applied in such areas so that they appear smoothly changing. In general, the quantization artifacts look like steps within a large slowly changing region, but identifying them in a natural image is a difficult because it is required to distinguish whether they are caused by the quantization of smoothly changing areas or it is exactly the scene. In addition, the process becomes more complicated due to the presence of additive noise introduced by the digitization device. The presence of noise makes the areas containing quantization artifacts look like small detailed regions. If a noisy area is detected as an area containing quantization artifact, the smoothing process removes the noise as well as quantization layers.
Sometimes a smoothly changing area includes stage-like artifacts even when the luminance of the neighboring pixels is only changing by the smallest possible step. In this case, a higher precision content of the smoothly changing area is desired in order to eliminate the quantization artifacts. With the higher precision content, halftoning techniques can be used (e.g. error diffusion or spatial dithering), to quantize the higher precision content to the current bit depth. The quantization artifacts will no longer be seen on the halftoned image due to the spatial averaging characteristics of human visual system.